For the instance segmentation, the MASK R-CNN artificial neural network was employed. This type of network is used in multiple applications where detection accuracy is required, especially for particles with complex shapes [1]}, [2]}. We have recently applied MASK R-CNN to track the particle positions and orientations in a 3D gas of elongated particles [3]}. To build the data set, around 30 frames with 300 to 400 particles each were manually annotated. Then, the MASK R-CNN pre-trained on the MS COCO [4]} image data set was trained for around 100 epochs on the augmented images.
